Multi-Agent Task Completion Benchmark Q3 2026
Thesis
Role-based multi-agent crews outperform single-agent approaches by 40–60% on complex multi-step tasks requiring diverse tool access.
What's inside
- Benchmark across 12 task categories with standardized evaluation
- Crew composition strategies and role specialization effects
- Cost-per-task comparison across model providers
Claims sourced from this document
tool calling protocol
Custom tool decorator protocol, MCP via adapter.
asserted eval harness maturity
Benchmark suite for multi-agent task completion.
asserted model agnosticism
Supports major providers via LiteLLM integration.
asserted license obligations
Apache-2.0 for core framework.
evidenced